Skill UI

A skill for creating, editing, validating, syncing, and troubleshooting n8n workflows using n8n-as-code. Manages workspace environments, local instances, tunnels, and workflow operations through command-line interfaces. Supports environment configuration, API key management, and workflow lifecycle management.

PDFtk Server is a powerful command-line tool designed for comprehensive manipulation and processing of PDF documents. It allows users to programmatically merge, split, rotate, secure (encrypt/decrypt), fill forms, apply watermarks, extract metadata, repair corrupted files, and much more. Ideal for automation scripts, batch processing, and any scenario requiring robust, scripted PDF handling from the terminal.

Provides comprehensive command-line management for all Azure DevOps resources. Users can manage projects, repositories, CI/CD pipelines, pull requests, work items, and artifacts using the Azure CLI with the dedicated extension. This tool is essential for automation scripting, integration testing, and streamlining complete DevOps workflows.

This lightweight, dependency-free script integrates with Gmail via standalone OAuth authentication, requiring no external server. It allows users to perform comprehensive operations—including searching, reading content, sending emails (with CC/BCC/HTML support), and modifying labels—directly from the command line. It is ideal for automating complex inbox workflows and batch processing tasks for Google Workspace accounts.

This skill provides comprehensive guidelines for contributing and managing commands within VS Code extensions. It covers crucial best practices, including naming conventions, defining visibility (e.g., Command Palette vs. Side Bar), and structuring commands for optimal user experience. Use this when adding, updating, or understanding the architectural requirements for extension commands.

This guide provides comprehensive guidelines for localizing all aspects of VS Code extensions. It covers best practices for handling configurations (settings, commands, menus), user-facing string resources, and walkthrough content. Developers can use this skill to ensure their extensions are properly adapted and functional for multiple languages.

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

This guideline establishes a strict principle: never claim completion, success, or fix status without fresh, verifiable evidence. It mandates running explicit verification commands (like tests or linters) and presenting the full output and exit codes to support any assertion of work completion. It helps prevent overconfidence and reliance on assumption or proxy reports.

Acontext serves as a robust memory layer for production-grade AI agents. It provides persistent sessions, disk-based storage, and sophisticated learning spaces that distill complex conversations into reusable, structured skills. Users can manage the entire system—from project setup and login to skill uploading—via a powerful Command Line Interface (CLI) and API, significantly enhancing agents' contextual understanding and long-term knowledge retention.

A powerful utility for performing semantic searches across a large knowledge base of 105K+ skill cards. It allows users to find the most relevant skills based on natural language queries, supporting both Python API integration and Command Line Interface (CLI). This tool is zero-dependency and highly efficient for skill discovery and knowledge retrieval in development workflows.

A comprehensive Python command-line toolkit for processing and visualizing high-throughput sequencing data including ChIP-seq, RNA-seq, and ATAC-seq. Performs quality control, normalization, sample comparison, and generates publication-quality genomic visualizations with bigWig conversion and heatmap profiles.

gget is a command-line and Python package providing unified access to over 20 genomic databases and analysis methods. It supports querying gene information, sequence analysis, protein structures, viral sequences, expression data, and disease associations. Suitable for interactive exploration and simple queries, offering both CLI and Python function interfaces for bioinformatics workflows.